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Reproducibility in pharmacometrics applied in a phase III trial of BCG-vaccination for COVID-19

Van Wijk, Rob C, 1991- (författare)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap
Mockeliunas, Laurynas (författare)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap
van den Hoogen, Gerben (författare)
TASK, Cape Town, South Africa.
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Upton, Caryn M. (författare)
TASK, Cape Town, South Africa.
Diacon, Andreas H. (författare)
TASK, Cape Town, South Africa.
Simonsson, Ulrika S. H., Professor (författare)
Uppsala universitet,Institutionen för farmaceutisk biovetenskap
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 (creator_code:org_t)
Springer Nature, 2023
2023
Engelska.
Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Large clinical trials often generate complex and large datasets which need to be presented frequently throughout the trial for interim analysis or to inform a data safety monitory board (DSMB). In addition, reliable and traceability are required to ensure reproducibility in pharmacometric data analysis. A reproducible pharmacometric analysis workflow was developed during a large clinical trial involving 1000 participants over one year testing Bacillus Calmette-Guerin (BCG) (re)vaccination in coronavirus disease 2019 (COVID-19) morbidity and mortality in frontline health care workers. The workflow was designed to review data iteratively during the trial, compile frequent reports to the DSMB, and prepare for rapid pharmacometric analysis. Clinical trial datasets (n = 41) were transferred iteratively throughout the trial for review. An RMarkdown based pharmacometric processing script was written to automatically generate reports for evaluation by the DSMB. Reports were compiled, reviewed, and sent to the DSMB on average three days after the data cut-off, reflecting the trial progress in real-time. The script was also utilized to prepare for the trial pharmacometric analyses. The same source data was used to create analysis datasets in NONMEM format and to support model script development. The primary endpoint analysis was completed three days after data lock and unblinding, and the secondary endpoint analyses two weeks later. The constructive collaboration between clinical, data management, and pharmacometric teams enabled this efficient, timely, and reproducible pharmacometrics workflow.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmaceutiska vetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmaceutical Sciences (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)

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